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A Practical Approach for Road Quality Estimation using Smartphone based Inertial Data: IMU data processing pipeline to estimate road quality

Published: 10 June 2022 Publication History

Abstract

The tight financial situation in many municipalities does not allow them to record and evaluate the condition of their own transport infrastructure in detail. The present rule-based road quality estimation methods are outdated, very expensive and less accurate. The only subjective and non-recurring documentation leads to the fact that there is no resilient data basis for intelligent, data-based condition forecasts, which would actually be possible with methods of artificial intelligence (AI) and machine learning (ML). The considerable potential for cost minimization that such forecasts would open up via maintenance optimization remains untapped. In this research work, we demonstrate a road quality estimation system given the Inertial Measurement Unit (IMU) data from smartphone mounted on a vehicle. The system consists of a data preprocessing pipeline which removes many uncertainties along with more accurate geo-referencing of the raw data, and training a machine learning model to estimate road quality in terms of a continuous variable. Route quality information is gathered together with GPS tracking using the IMU data coming from smartphone mounted on a vehicle. The ground-truth (road quality) is obtained using conventional road quality measurement system. Next, distinctive features are obtained from the IMU raw data. Consequently, a machine learning model is trained to estimate the road quality from the obtained features with high performance.

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  • (2023)Estimating road friction from kinematic summaries at curved sections2023 IEEE Conference on Control Technology and Applications (CCTA)10.1109/CCTA54093.2023.10253194(307-314)Online publication date: 16-Aug-2023

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          cover image ACM Other conferences
          ICMLT '22: Proceedings of the 2022 7th International Conference on Machine Learning Technologies
          March 2022
          291 pages
          ISBN:9781450395748
          DOI:10.1145/3529399
          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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          Publication History

          Published: 10 June 2022

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          Author Tags

          1. Feature extraction
          2. Predictive maintenance
          3. Road quality estimation
          4. Sensor data processing

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          • (2023)Estimating road friction from kinematic summaries at curved sections2023 IEEE Conference on Control Technology and Applications (CCTA)10.1109/CCTA54093.2023.10253194(307-314)Online publication date: 16-Aug-2023

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